Over the decades, healthcare industries have been gathering an increasing amount of data. But most of it remains unorganized and unused due to stringent laws. But even after such laws have been changed, it is not being leveraged, properly. This gamut of data can be used to build solutions that can bring down the complexity in healthcare diagnostics.
But before delving further, we must understand the nature of data in the current day and time. It can be described as driven by 3 V’s – volume, velocity, and variety. Data is accumulating at a great volume every day with an increasing velocity and its varieties are diversifying every day as we speak. All the 3 V’s hold significance as they help narrow down the possibilities through data analytics and AI / ML algorithms.
Even then, previously the IT infrastructure was not ready to support data in such scale and measure (i.e., petabytes & exabytes). Now that the current infrastructure can support working with these three Vs of data, it has paved way for many solutions using data mining techniques and then comparing the results against real-time diagnostics. The resulting outputs have cut down the time and reduced a significant amount of burden for healthcare personnel. With more data pouring in, the accuracy levels are only getting better!
Despite knowing all of this, it is the adaption that is key. One must have a relevant understanding of building solutions ground up using the expertise in Artificial Intelligence and Machine Learning. They must be ready to narrow down the results through multiple iterations in a swift manner leveraging all tools at hand. Solutions such as ‘GynEye by Suja‘ are doing this successfully by reducing the margin of error in diagnosing cervical cancer and other abnormalities in remote setups. So, the decision remains with the players in the healthcare industry to move from legacy tools that no more hold significance and move towards the tools of tomorrow.
Be prepared for tomorrow. Step into the future, now with Suja’s expertise!